对于AI与车联网的融合发展，我将在本文中对几篇文献综述中所提到的信息进行总结，并将在最后进行整体归纳。在此向文献综述的作者们致以崇高的谢意。
Popular Content Distribution in Public Transportation Using Artificial Intelligence Techniques ——2019.1.8
V2X有三大应用场景：traffic efficiency, road safety, energy efficiency
| 标题 | 总结 |
|---|---|
| Machine Learning for Vehicular Networks: Recent Advances and Application Examples IEEE Vehicular Technology Magazine （SCI 2区）- 2018 |
【文献综述】车联网研究现状及应用场景。【已下载】 |
| Connected Vehicles: Solutions and Challenges IEEE Internet of Things Journal （SCI 1区）- 2014 |
The challenges and various solutions to connected vehicles【已下载】 |
| Vehicle Safety Improvement through Deep Learning and Mobile Sensing IEEE Network（SCI 1区）- 2018 |
identifies two main challenges in this context:1) driving safety analysis, and 2) road safety analysis. They proposed a new deep learning framework known as DeepRSI, to conduct real-time predictions of the road safety【已下载】 |
| Driver information system: a combination of augmented reality, deep learning and vehicular Ad-hoc networks MULTIMEDIA TOOLS AND APPLICATIONS （SCI 3-4区）- 2017.8.3 |
applied deep learning to improve vehicle safety and comfort by performing human factors assessment and displaying the surrounding information to the drivers【已下载】 |
| A linear model predictive planning approach for overtaking manoeuvres under possible collision circum- stances 2018 IEEE Intelligent Vehicles Symposium (IV) （顶会） |
【已下载】 |
| Vehicle trajectory prediction with Gaussian process regression in connected vehicle environment 2018 IEEE Intelligent Vehicles Symposium (IV) （顶会） |
【已下载】 |
| Cooperative collision avoidance by sharing vehicular subsystem data 2018 IEEE Intelligent Vehicles Symposium (IV) （顶会） |
【已下载】 |
| LTE Connectivity and Vehicular Traffic Prediction Based on Machine Learning Approaches 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall) |
【已下载】 |
| Deep Sequence Learning with Auxiliary Information arxiv - 2018【浙大】 |
【已下载】 |
| Decision-Theoretic Cooperative Parking for Connected Vehicles: an Investigation 2018 IEEE Intelligent Vehicles Symposium (IV) （顶会） |
a decentralized coordination approach was introduced to search the car parking spots, which is applicable to large car park areas.【已下载】 |
| Spatio-Temporal Network Traffic Estimation and Anomaly Detection Based on Convolutional Neural Network in Vehicular Ad-Hoc Networks IEEE ACCESS 2018 （SCI 2区） |
SPATIO-TEMPORAL NETWORK TRAFFIC ESTIMATION IN VANETs【已下载】 |
| Deep reinforcement learning for traffic light control in vehicular networks Arxiv 2018 |
In this work the traffic intersection scenario contains multiple phases, which represents a high-dimension action space. The work also guarantees that the traffic signal time smoothly changes between two neighboring actions.【已下载】 |
| Adaptive Traffic Signal Control with Deep Recurrent Q-learning 2018 IEEE Intelligent Vehicles Symposium (IV) 顶会 |
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| Traffic flow prediction with big data: A deep learning approach IEEE Transactions on Intelligent Transportation Systems 2015 |
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| Deep sequence learning with auxiliary information for traffic prediction Arxiv 2018 |
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| A swarm algorithm for collaborative traffic in vehicular networks Vehicular Communications 2018（SCI 2区） |
【已下载】 |
| A Demand-Supply Oriented Taxi Recommendation System for Vehicular Social Networks IEEE ACCESS 2018 （SCI 2区） |
【已下载】 |
待解决问题：
- traffic flow prediction
感兴趣问题：
- 防碰撞